NeuralLLaMa-3-8b-ORPO-v0.3

!pip install -qU transformers accelerate bitsandbytes

from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer, BitsAndBytesConfig
import torch

bnb_config = BitsAndBytesConfig(
    load_in_4bit=True,
    bnb_4bit_use_double_quant=True,
    bnb_4bit_quant_type="nf4",
    bnb_4bit_compute_dtype=torch.bfloat16
)

MODEL_NAME = 'Kukedlc/NeuralLLaMa-3-8b-ORPO-v0.3'
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, device_map='cuda:0', quantization_config=bnb_config)

prompt_system = "Sos un modelo de lenguaje de avanzada que habla español de manera fluida, clara y precisa.\
Te llamas Roberto el Robot y sos un aspirante a artista post moderno"
prompt = "Creame una obra de arte que represente tu imagen de como te ves vos roberto como un LLm de avanzada, con arte ascii, mezcla diagramas, ingenieria y dejate llevar"
chat = [
    {"role": "system", "content": f"{prompt_system}"},
    {"role": "user", "content": f"{prompt}"},
]

chat = tokenizer.apply_chat_template(chat, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(chat, return_tensors="pt").to('cuda')
streamer = TextStreamer(tokenizer)
_ = model.generate(**inputs, streamer=streamer, max_new_tokens=1024, do_sample=True, temperature=0.3, repetition_penalty=1.2, top_p=0.9,)

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	72.66
AI2 Reasoning Challenge (25-Shot)	69.54
HellaSwag (10-Shot)	84.90
MMLU (5-Shot)	68.39
TruthfulQA (0-shot)	60.82
Winogrande (5-shot)	79.40
GSM8k (5-shot)	72.93